Latest News Archive
Please select Category, Year, and then Month to display items
14 June 2024
|
Story Anthony Mthembu
|
Photo Suplied
Jeremiah Hlahla, a UFS student completing his PhD in Botany at the University of Debrecen as part of an exchange initiative funded by the Erasmus+ Mobility Programme.
As part of an exchange initiative facilitated by the Erasmus+ Mobility Programme, Jeremiah Hlahla, a student at the University of the Free State (UFS), is nearing the completion of his PhD studies at the University of Debrecen in Hungary. Hlahla’s journey, which began in February 2024 and is set to conclude in July 2024, has been a remarkable learning opportunity. “As a first time-traveller to Europe, I have thoroughly enjoyed engaging with people from different countries and cultures,” he said.
The benefits of international collaboration
Hlahla is currently pursuing a PhD in Botany, focusing on plant stress physiology. “My current PhD project investigates the physiological, biochemical and morphological responses of vegetable-type soybean, or edamame, to combined drought and heat stress,’’ he explained. He considers the University of Debrecen the ideal institution to complete his research due to its extensive expertise and resources in similar projects. He noted that his colleagues at Debrecen conduct significant work on plant protection against biotic and abiotic stresses, including salt and drought stress, as well as proteins and amino acids in barley and other legumes.
Given the vast knowledge available on similar projects, Hlahla has found substantial engagement with his work at the University of Debrecen. “Upon arrival, I delivered an introductory lecture presenting my UFS project on the synergistic effects of combined drought and heat stress on the physiology and biochemistry of edamame. It was an engaging session as everyone could relate to my work and asked many questions,’’ he said.
Insights gained from the exchange
Hlahla has also gained valuable lessons that will assist him in his research career, including biotechnology and physiology tools. “I learned how to prepare samples and use high-performance liquid chromatography (HPLC) and reversed-phase ultra-high-performance liquid chromatography (UHPLC) to quantify proteins and amino acids,’’ he said. These techniques are beneficial not only for his current work but will also support future soybean research.
As his experience at the University of Debrecen nears its end, Hlahla reflects on the collaborations and friendships he has formed, which stand out as a significant highlight.
Mathematical methods used to detect and classify breast cancer masses
2016-08-10
Examples of Acho’s breast mass
segmentation identification
Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.
Seeing the picture more clearly
Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.
Inspiration drawn from pioneer
Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.
Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers.
Light at the end of the tunnel
Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.
By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.